A guide to robust statistical methods / Rand R. Wilcox.
Wilcox, Rand R., author.
2023
QA276 .W55 2023
Available Online

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Title A guide to robust statistical methods / Rand R. Wilcox.
Author Wilcox, Rand R., author.
ISBN 9783031417139 electronic book
3031417135 electronic book
9783031417122
3031417127
DOI https://doi.org/10.1007/978-3-031-41713-9
Published Cham : Springer, 2023.
Language English
Description 1 online resource (xvii, 326 pages) : illustrations
Other Standard Identifiers 10.1007/978-3-031-41713-9 doi
Call Number QA276 .W55 2023
Summary Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true -- but they continue to perform well in situations where classic methods perform poorly. This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data. The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 30, 2023).
Available in Other Form Print version: 9783031417122
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1. Introduction
2. The one-sample case
3. Comparing two independent groups
4. Comparing two dependent groups
5. Comparing multiple independent groups
6. Comparing multiple dependent groups
7. Robust regression estimators
8. Inferential methods based on robust regression estimators
9. Measures of association
10. Comparing groups when there is a covariate.

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